Activities per year
Project Details
Description
The vision of the Hub is to create ground-breaking embedded metrology and universal metrology informatics systems to be applied across the manufacturing value chain. This encompasses a paradigm shift in measurement technologies, embedded sensors/instrumentation and metrology solutions. A unified approach to creating new, scientifically-validated measurement technologies in manufacturing will lead to critical underpinning solutions to stimulate significant growth in the UK's productivity and facilitate future factories.
Global manufacturing is evolving through disruptive technologies towards a goal of autonomous production, with manufacturing value-chains increasingly digitised. Future factories must be faster, more responsive and closer to customers as manufacturing is driven towards mass customisation of lower-cost products on demand. Metrology is crucial in underpinning quality, productivity and efficiency gains under these new manufacturing paradigms.
The Advanced Metrology Hub brings together a multi-disciplinary team from Huddersfield with spokes at Loughborough, Bath and Sheffield universities, with fundamental support from NPL. Expertise in Engineering, Mathematics, Physics and Computer Science will address the grand challenges in advanced metrology and the Hub's vision through two key research themes and parallel platform activities:
Theme I - Embedded Metrology will build sound technological foundations by bridging four formidable gaps in process- and component-embedded metrology. This covers: physical limits on the depth of field; high dynamic range measurement; real-time dynamic data acquisition in optical sensor/instruments; and robust, adaptive, scalable models for real-time control systems using sensor networks with different physical properties under time-discontinuous conditions.
Theme II - Metrology Data analytics will create a smart knowledge system to unify metrology language, understanding, and usage between design, production and verification for geometrical products manufacturing; Establishment of data analytics systems to extract maximal information from measurement data going beyond state-of-the-art for optimisation of the manufacturing process to include system validation and product monitoring.
Platform research activities will underpin the Hub's vision and core research programmes, stimulate new areas of research and support the progression of fundamental and early-stage research towards deployment and impact activities over the Hub's lifetime.
In the early stage of the Hub, the core research programme will focus on four categories (Next generation of surface metrology; Metrology technologies and applications; In-process metrology and Machine-tool and large volume metrology) to meet UK industry's strategic agenda and facilitate their new products.
The resulting pervasive embedding and integration of manufacturing metrology by the Hub will have far reaching implications for UK manufacturing as maximum improvements in product quality, minimization of waste/rework, and minimum lead-times will ultimately deliver direct productivity benefits and improved competitiveness. These benefits will be achieved by significantly reducing (by 50% to 75%) verification cost across a wide swathe of manufacture sectors (e.g. aerospace, automotive, electronics, energy, medical devices, optics, precision engineering) where the current cost of verification is high (up to 20% of total costs) and where product quality and performance is critical.
Global manufacturing is evolving through disruptive technologies towards a goal of autonomous production, with manufacturing value-chains increasingly digitised. Future factories must be faster, more responsive and closer to customers as manufacturing is driven towards mass customisation of lower-cost products on demand. Metrology is crucial in underpinning quality, productivity and efficiency gains under these new manufacturing paradigms.
The Advanced Metrology Hub brings together a multi-disciplinary team from Huddersfield with spokes at Loughborough, Bath and Sheffield universities, with fundamental support from NPL. Expertise in Engineering, Mathematics, Physics and Computer Science will address the grand challenges in advanced metrology and the Hub's vision through two key research themes and parallel platform activities:
Theme I - Embedded Metrology will build sound technological foundations by bridging four formidable gaps in process- and component-embedded metrology. This covers: physical limits on the depth of field; high dynamic range measurement; real-time dynamic data acquisition in optical sensor/instruments; and robust, adaptive, scalable models for real-time control systems using sensor networks with different physical properties under time-discontinuous conditions.
Theme II - Metrology Data analytics will create a smart knowledge system to unify metrology language, understanding, and usage between design, production and verification for geometrical products manufacturing; Establishment of data analytics systems to extract maximal information from measurement data going beyond state-of-the-art for optimisation of the manufacturing process to include system validation and product monitoring.
Platform research activities will underpin the Hub's vision and core research programmes, stimulate new areas of research and support the progression of fundamental and early-stage research towards deployment and impact activities over the Hub's lifetime.
In the early stage of the Hub, the core research programme will focus on four categories (Next generation of surface metrology; Metrology technologies and applications; In-process metrology and Machine-tool and large volume metrology) to meet UK industry's strategic agenda and facilitate their new products.
The resulting pervasive embedding and integration of manufacturing metrology by the Hub will have far reaching implications for UK manufacturing as maximum improvements in product quality, minimization of waste/rework, and minimum lead-times will ultimately deliver direct productivity benefits and improved competitiveness. These benefits will be achieved by significantly reducing (by 50% to 75%) verification cost across a wide swathe of manufacture sectors (e.g. aerospace, automotive, electronics, energy, medical devices, optics, precision engineering) where the current cost of verification is high (up to 20% of total costs) and where product quality and performance is critical.
Status | Finished |
---|---|
Effective start/end date | 1/10/16 → 30/09/23 |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
-
EUSPEN Special Interest Group Meeting: Thermal Issues 2024
Andrew Longstaff (Chair)
13 Mar 2024 → 14 Mar 2024Activity: Participating in or organising an event types › Organising a conference, workshop, ...
-
15th International Conference and Exhibition on Laser Metrology, Coordinate Measuring Machine and Machine Tool Performance
Andrew Longstaff (Chair)
14 Mar 2023 → 15 Mar 2023Activity: Participating in or organising an event types › Organising a conference, workshop, ...
-
EUSPEN Special Interest Group Meeting: Thermal Issues 2022
Andrew Longstaff (Member of programme committee)
22 Mar 2022 → 23 Mar 2022Activity: Participating in or organising an event types › Organising a conference, workshop, ...
-
Novel Robot Arm Concept for Lightweighting High Performance Machinery
John, K., Fletcher, S., Furness, T., Longstaff, A. & Needham, P., 30 Jan 2024, In: Journal of Machine Design and Automation Intelligence. 2, 1, 14 p., 20230006.Research output: Contribution to journal › Article › peer-review
Open Access -
A multi-criterion three-way decision-making method under linguistic interval-valued intuitionistic fuzzy environment
Qin, Y., Qi, Q., Shi, P., Scott, P. & Jiang, J., 1 Oct 2023, In: Journal of Ambient Intelligence and Humanized Computing. 14, 10, p. 13915-13929 15 p.Research output: Contribution to journal › Article › peer-review
Open Access4 Citations (Scopus) -
Learn to Rotate: Part Orientation for Reducing Support Volume via Generalizable Reinforcement Learning
Shi, P., Qi, Q., Qin, Y., Meng, F., Lou, S., Scott, P. & Jiang, J., 1 Dec 2023, In: IEEE Transactions on Industrial Informatics. 19, 12, p. 11687-11700 14 p., 10054468.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (Scopus)
Projects
- 1 Finished
-
ESPRC Centre for Innovative Manufacturing in Advanced Metrology
Jiang, J., Blunt, L., Longstaff, A., Towns-Andrews, L., Scott, P., Myers, A., Fletcher, S. & Ball, A.
1/09/11 → 28/02/17
Project: Research